Radiotherapy-induced bone deterioration is exacerbated in diabetic rats treated with streptozotocin
Bibliographic record
Abstract
Following radiotherapy, patients have decreased bone mass and increased risk of fragility fractures. Diabetes mellitus (DM) is also reported to have detrimental effects on bone architecture and quality. However, no clinical or experimental study has systematically characterized the bone phenotype of the diabetic patients following radiotherapy. After one month of streptozotocin injection, three-month-old male rats were subjected to focal radiotherapy (8 Gy, twice, at days 1 and 3), and then bone mass, microarchitecture, and turnover as well as bone cell activities were evaluated at 2 months post-irradiation. Micro-computed tomography results demonstrated that DM rats exhibited greater deterioration in trabecular bone mass and microarchitecture following irradiation compared with the damage to bone structure induced by DM or radiotherapy. The serum biochemical, bone histomorphometric, and gene expression assays revealed that DM combined with radiotherapy showed lower bone formation rate, osteoblast number on bone surface, and expression of osteoblast-related markers (ALP, Runx2, Osx, and Col-1) compared with DM or irradiation alone. DM plus irradiation also caused higher bone resorption rate, osteoclast number on bone surface, and expression of osteoclast-specific markers (TRAP, cathepsin K, and calcitonin receptor) than DM or irradiation treatment alone. Moreover, lower osteocyte survival and higher expression of Sost and DKK1 genes (two negative modulators of Wnt signaling) were observed in rats with combined DM and radiotherapy. Together, these findings revealed a higher deterioration of the diabetic skeleton following radiotherapy, and emphasized the clinical importance of health maintenance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".